The present invention relates to three-dimensional reconstruction of an image from a set of cone beam X-ray projections, and more particularly, to systems for and methods of reconstructing a three-dimensional image corresponding to a volume segment that is part of a longer object.
Three-dimensional (3D) reconstruction algorithms are being developed for future scanners characterized by large cone angles. These algorithms can be clinically useful only if they can be used to reconstruct a volume within the patient (i.e., a region of interest—“ROI”), without having to scan the entire length of the patient. If the entire length of the patient is not scanned, then data truncation occurs in the axial direction of the scan. This data truncation gives rise to a difficulty in image reconstruction referred to herein as the “long object problem,” illustrated in FIG. 1. It is important to observe that this truncation is axial, i.e., perpendicular to the plane of the X-ray fan beam, and not within the plane of the fan beam. Thus, all of the data necessary to reconstruct the image slices within the ROI are present, even when the scan is limited to a volume slightly greater than the ROI.
Prior art reconstruction algorithms exist to solve the long-object problem, but the mathematical expressions of these algorithms are complicated and therefore difficult to implement. Such reconstruction algorithms typically handle the truncation that occurs at the edges of the ROI by either (1) imposing special conditions to include or exclude certain data, or (2) including boundary terms that are difficult to evaluate. Computer implementations of the special conditions or the boundary terms also give rise to image artifacts, partially due to the data quantization that occurs as a result of sampling.
It is an object of the present invention to substantially overcome the above-identified disadvantages and drawbacks of the prior art.